Decision making under uncertainty using PEES–fuzzy AHP–fuzzy TOPSIS methodology for landfill location selection |
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Authors: | Mohamed Hanine Omar Boutkhoum Abderrafie El Maknissi Abdessadek Tikniouine Tarik Agouti |
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Institution: | 1.Laboratory of Engineering and Information Systems, Department of Computer Science, Faculty of Sciences Semlalia,Cadi Ayyad University,Marrakesh,Morocco;2.Department of Geography,Polydisciplinary Faculty,Safi,Morocco;3.Team of Telecommunications and Computer Networks, Faculty of Sciences Semlalia,Cadi Ayyad University,Marrakesh,Morocco |
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Abstract: | The location selection for landfill municipal solid waste is an important issue in waste management. Selection of the optimal location requires consideration of multiple alternative solutions and evaluation factors because of system complexity. Further, ranking of the alternative locations and selection of the most optimal and efficient locations for landfill waste are an important multi-criteria decision-making problem. In this study, the candidate locations for landfill are determined based on Political, Economical, Environmental and Social factors are assessed through decision-makers’ opinion and by the methodology that incorporates fuzzy analytic hierarchy process (fuzzy AHP) and fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS). Specifically, the fuzzy AHP technique is applied to determine the weights of selected criteria impacting the location selection process, and the fuzzy AHP is adapted to model the linguistic vagueness and ambiguity, which can also be expressed as triangular fuzzy numbers. Furthermore, fuzzy TOPSIS technique is employed to rank the alternative locations. The applicability of this methodology is demonstrated by a case study of landfill waste location selection in the region of Casablanca, Morocco, and the results are compared with other techniques. Finally, to complete the treatment, a sensitivity analysis is performed to examine the impact of the preferences given by decision-makers to choose the best location. |
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